Advanced AI Engr

As an Advanced AI Engineer , you will design, develop, and deploy cutting-edge AI solutions with a strong focus on Generative AI (GenAI) and Agentic AI systems . You will build intelligent, autonomous AI agents using modern orchestration frameworks such as LangChain, LangGraph, and Databricks Mosaic AI Agent Framework , delivering scalable, secure, and production-ready AI systems tightly integrated with enterprise workflows.

You will collaborate closely with cross-functional teams to identify high-impact AI use cases, architect end-to-end solutions, and operationalize AI at scale using cloud platforms and MLOps best practices.

Key Responsibilities

• Design, develop, and optimize Generative AI and Agentic AI solutions for real-world, enterprise-grade applications.
• Build and orchestrate AI-powered agents and multi-agent systems using frameworks such as LangChain, LangGraph, and Databricks Mosaic AI Agent Framework .
• Architect and implement end-to-end AI pipelines , including data ingestion, feature engineering, model training, evaluation, and inference.
• Collaborate with product, data, platform, and business stakeholders to identify AI use cases and translate requirements into scalable AI solutions.
• Deploy and manage AI models and agents on cloud platforms (Azure, AWS, or GCP) using containerization (Docker/Kubernetes) and modern MLOps practices.
• Implement model monitoring, observability, and performance tracking to ensure accuracy, reliability, and responsible AI usage in production.
• Leverage MLflow for experiment tracking, model versioning, and lifecycle management.
• Utilize Databricks AI/ML Platform , including Unity Catalog , for governed data access, feature management, and secure AI deployments.
• Ensure AI systems meet enterprise standards for scalability, security, compliance, and maintainability.
• Stay current with emerging AI technologies, frameworks, and research, driving innovation and continuous improvement across AI solutions.

YOU MUST HAVE

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field .
• 6+ years of hands-on experience in AI/ML development, deployment, and productionization.
• Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and Scikit-learn .
• Proven hands-on experience building LLM-based applications and AI agents using LangChain, LangGraph , or similar frameworks.
• Experience deploying AI solutions on Azure, AWS, or GCP , with a solid understanding of cloud-native architectures.
• Strong foundation in data structures, algorithms, and software engineering best practices .
• Experience implementing MLOps pipelines , including CI/CD, model versioning, and monitoring.
  

Preferred Skills & Experience

• Strong knowledge of Generative AI models , including Large Language Models (LLMs) and diffusion-based models.
• Expertise in prompt engineering , retrieval-augmented generation (RAG), and tool-augmented LLM workflows.
• Experience designing Agentic AI architectures , autonomous workflows, and multi-agent systems .
• Hands-on experience with Databricks Mosaic AI , MLflow , and Unity Catalog for governed AI development.
• Familiarity with CI/CD pipelines for AI/ML solutions and infrastructure-as-code practices.
• Strong problem-solving skills with the ability to design scalable and maintainable AI systems.
• Excellent communication skills, with the ability to explain complex AI concepts to both technical and non-technical stakeholders.